title: Dynamical system design for silicon neurons using phase reduction approach.
abstract: In the present paper, we apply a computer-aided phase reduction approach to dynamical system design for silicon neurons (SiNs). Firstly, we briefly review the dynamical system design for SiNs. Secondly, we summarize the phase response properties of circuit models of previous SiNs to clarify design criteria in our approach. From a viewpoint of the phase reduction theory, as a case study, we show how to tune circuit parameters of the resonate-and-fire neuron (RFN) circuit as a hybrid type SiN. Finally, we demonstrate delay-induced synchronization in a silicon spiking neural network that consists of the RFN circuits.
authors.forename: Kazuki
authors.initials: K
authors.lastname: Nakada
authors.forename: Keiji
authors.initials: K
authors.lastname: Miura
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Asai
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D003201:Computers; D001330:Electronic Data Processing; D016014:Linear Models; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D012825:Silicon / Q000737:chemistry*; D012984:Software
chemical_list: D012825:Silicon